April 2024 arXiv papers — page 123

Tapas Chatterjee, Sonam Garg

For a fixed prime $p$, Murty and Saradha (2008) studied the transcendental nature of special values of the $p$-adic digamma function, denoted as $\psi_p(r/p)+ \gamma_p$. This research was later extended by Chatterjee and Gun in 2014, who investigated the case of $\psi_p(r/p^n)+ \gamma_p$, for any integer $n>1$. In this article, we generalize their results fo

Thomas Pähtz, Yulan Chen, Jiafeng Xie, Rémi Monthiller

The study-to-study variability of bedload flux measurements in turbulent sediment transport borders an order of magnitude, even for idealized laboratory conditions. This uncertainty stems from physically poorly supported, empirical methods to account for channel geometry effects in the determination of the transport-driving bed shear stress, and from study-t

Tapas Chatterjee, Sonam Garg

In 2003, Zudilin presented a $q$-analogue of Euler's identity for one of the variants of $q$-double zeta function. This article focuses on exploring identities related to another variant of $q$-double zeta function and its star variant. Using a $q$-analogue of the Nielsen Reflexion Formula for $q>1$, we investigate identities involving different versions of

T. D. Kaladze, A. P. Misra

The stability of atmospheric stratified fluids is revisited to study the influence of the temperature-dependent density inhomogeneity due to thermal expansion in the Earth's lower atmosphere (with heights $0$ to $50$ km) under the action of gravity. Previous theory in the literature [Phys. Lett. A 480 (2023) 128990] is modified and advanced. It is found that

Jie Wang, Jing Lian, Minjie Ma, Junqiang Lei

Heart rate is an important physiological indicator of human health status. Existing remote heart rate measurement methods typically involve facial detection followed by signal extraction from the region of interest (ROI). These SOTA methods have three serious problems: (a) inaccuracies even failures in detection caused by environmental influences or subject

Muhammad Adeel Hafeez, Michael G. Madden, Ganesh Sistu, Ihsan Ullah

Depth estimation from 2D images is a common computer vision task that has applications in many fields including autonomous vehicles, scene understanding and robotics. The accuracy of a supervised depth estimation method mainly relies on the chosen loss function, the model architecture, quality of data and performance metrics. In this study, we propose a simp

Hakan Yekta Yatbaz, Mehrdad Dianati, Konstantinos Koufos, Roger Woodman

Monitoring the integrity of object detection for errors within the perception module of automated driving systems (ADS) is paramount for ensuring safety. Despite recent advancements in deep neural network (DNN)-based object detectors, their susceptibility to detection errors, particularly in the less-explored realm of 3D object detection, remains a significa

Paul S. Koh

Standard empirical tools for merger analysis assume price data, which are often unavailable. I characterize sufficient conditions for identifying the unilateral effects of mergers without price data using the first-order approach and merger simulation. Data on merging firms' revenues, margins, and revenue diversion ratios are sufficient to identify their gro

Giulio Chiribella, Kaumudibikash Goswami

We introduce two quantitative measures of the strength of causal relations in quantum theory and more general physical theories. These two measures, called the maximum and minimum causal effect, quantify the maximum and minimum changes in the output of a quantum process induced by changes in its input. The maximum and minimum causal effects possess useful pr

Maitraya Avadhut Desai, Xiuqiang He, Linbin Huang, Florian Dörfler

In this paper, we investigate the transient stability of a state-of-the-art grid-forming complex-droop control (i.e., dispatchable virtual oscillator control, dVOC) under current saturation. We quantify the saturation level of a converter by introducing the concept of degree of saturation (DoS), and we propose a provably stable current-limiting control with

Ming-Zhu Liu, Xi-Zhe Ling, Li-Sheng Geng

The two excited vector charmonium states $Y(4220)$ and $Y(4360)$ are difficult to be understood as pure $c\bar{c}$ charmonium states. Since they are located close to the mass thresholds of $\bar{D}D_{1}$ and $\bar{D}^*D_{1}$, they can be viewed as $\bar{D}D_{1}$ and $\bar{D}^*D_{1}$ molecules. Furthermore, recent studies indicated that the exotic states $X(3

T. Pietrangeli, C. Ybert, C. Cottin-Bizonne, F. Detcheverry

Run-and-tumble is a basic model of persistent motion and a motility strategy widespread in micro-organisms and individual cells. In many natural settings, movement occurs in the presence of confinement. While accumulation at the surface has been extensively studied, the transport parallel to the boundary has received less attention. We consider a run-and-tum

Dung Xuan Nguyen, Barbara Dietz

We study fluctuation properties in the energy spectra of finite-size honeycomb lattices, graphene billiards, subject to the Haldane-model onsite potential and next-nearest neighbor interaction at critical points, referred to as Haldane graphene billiards in the following. The billiards had the shapes of a rectangular billiard with integrable dynamics, one wi

Maria Fay, Frederik F. Flöther

For organizations to survive and flourish in the long term, innovation and novelty must be continually introduced, which is particularly true in today's rapidly changing world. This raises a variety of ethical and sustainability considerations that seldom receive the attention they deserve. Existing innovation adoption frameworks often focus on technological

Lei Sun, Zhengwei Tao, Youdi Li, Hiroshi Arakawa

The integration of Large Language Models (LLMs) and knowledge graphs (KGs) has achieved remarkable success in various natural language processing tasks. However, existing methodologies that integrate LLMs and KGs often navigate the task-solving process solely based on the LLM's analysis of the question, overlooking the rich cognitive potential inherent in th

Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Christopher C. Kaltenecker

The QUILT-1M dataset is the first openly available dataset containing images harvested from various online sources. While it provides a huge data variety, the image quality and composition is highly heterogeneous, impacting its utility for text-conditional image synthesis. We propose an automatic pipeline that provides predictions of the most common impuriti

Marc Saideh, Jean-Paul Jamont, Laurent Vercouter

Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike other domains, IoT offers several advantages and opportunities, such as the ability to collect real-time data through nume

Nicola Cantisani, Jan Lorenz Svensen, Ole Fink Hansen, John Bagterp Jørgensen

We present a novel dynamic model of a flash clay calciner. The model consists of thermophysical properties, reaction kinetics and stoichiometry, transport, mass and energy balances, and algebraic constraints. This gives rise to a system of partial differential-algebraic equations (PDAE). Spatial discretization is performed to convert the PDAEs into a system

Andrés Lou, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Víctor M. Sánchez-Cartagena

The Mayan languages comprise a language family with an ancient history, millions of speakers, and immense cultural value, that, nevertheless, remains severely underrepresented in terms of resources and global exposure. In this paper we develop, curate, and publicly release a set of corpora in several Mayan languages spoken in Guatemala and Southern Mexico, w

Lorenzo Pagliara, Enrico Ferrentino, Andrea Chiacchio, Giovanni Russo

Haptic teleoperations play a key role in extending human capabilities to perform complex tasks remotely, employing a robotic system. The impact of haptics is far-reaching and can improve the sensory awareness and motor accuracy of the operator. In this context, a key challenge is attaining a natural, stable and safe haptic human-robot interaction. Achieving

Yuetan Chu, Gongning Luo, Longxi Zhou, Shaodong Cao

Pulmonary artery-vein segmentation is crucial for disease diagnosis and surgical planning and is traditionally achieved by Computed Tomography Pulmonary Angiography (CTPA). However, concerns regarding adverse health effects from contrast agents used in CTPA have constrained its clinical utility. In contrast, identifying arteries and veins using non-contrast

Kalp Pandya, Devdeep Shetranjiwala, Naisargi Savaliya, Manish K. Gupta

The VT and Helberg codes, both in binary and non-binary forms, stand as elegant solutions for rectifying insertion and deletion errors. In this paper we consider the quaternary versions of these codes. It is well known that many optimal binary non-linear codes like Kerdock and Prepreta can be depicted as Gray images (isometry) of codes defined over $\mathbb{

Cedric Gillmann, Giada N. Arney, Guillaume Avice, M. D. Dyar

After decades of relative neglect, interest in Venus surges anew in the planetary science community and the public. New missions are planned and selected, and will pave the way to the decade of Venus, as new observations allow us to uncover some of the many mysteries our closest Solar System neighbor still harbors. Building on the legacy of past works, here,

Miruna-Alexandra Gafencu, Yordanka Velikova, Mahdi Saleh, Tamas Ungi

Purpose: Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information. While performing US-based diagnosis or investigation, medical professionals therefore create a mental map of the 3D anatomy. In this work, we aim to replicate this process

Nicolò Di Domenico, Guido Borghi, Annalisa Franco, Davide Maltoni

The advent of morphing attacks has posed significant security concerns for automated Face Recognition systems, raising the pressing need for robust and effective Morphing Attack Detection (MAD) methods able to effectively address this issue. In this paper, we focus on Differential MAD (D-MAD), where a trusted live capture, usually representing the criminal,

Ming-Sheng Liu, Hao XU

In this paper, we first establish two versions of Landau-Bloch type theorem for $(K,K')$-elliptic harmonic mappings with a bounded minimum distortion. Next, we provide several coefficient estimates and a conjecture for $(K,K')$-elliptic harmonic mappings. Then, we establish three new versions of Landau-Bloch type theorem for sense-preserving harmonic mapping

Danyer Perez Adan, Luis Ignacio Estevez Banos, Tony Cass, Bjoern Felkers

In August 2023, IT experts and scientists came together for a workshop to discuss the possibilities of building a computer cluster fully on renewable energies, as a test-case at Havana University in Cuba. The discussion covered the scientific needs for a computer cluster for particle physics at the InSTEC institute at Havana University, the possibilities to

Poulami Sinhamahapatra, Franziska Schwaiger, Shirsha Bose, Huiyu Wang

Detecting and localising unknown or out-of-distribution (OOD) objects in any scene can be a challenging task in vision, particularly in safety-critical cases involving autonomous systems like automated vehicles or trains. Supervised anomaly segmentation or open-world object detection models depend on training on exhaustively annotated datasets for every doma

Bin Cheng, Jonathan Fürst, Tobias Jacobs, Celia Garrido-Hidalgo

The creation of high-quality ontologies is crucial for data integration and knowledge-based reasoning, specifically in the context of the rising data economy. However, automatic ontology matchers are often bound to the heuristics they are based on, leaving many matches unidentified. Interactive ontology matching systems involving human experts have been intr

Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low

Physics-Informed Neural Networks (PINNs), which incorporate PDEs as soft constraints, train with a composite loss function that contains multiple training point types: different types of collocation points chosen during training to enforce each PDE and initial/boundary conditions, and experimental points which are usually costly to obtain via experiments or

Hajo Holzmann, Bernhard Klar

We show that established performance metrics in binary classification, such as Matthews' correlation coefficient (MCC), Cohen's $κ$, the F-score or the Jaccard similarity coefficient are not robust to class imbalance in the sense that if the proportion of the minority class tends to $0$, the true positive rate (TPR) of the Bayes classifier under thes

Cécile Huneau, Jonathan Luk

We review recent mathematical results concerning the high-frequency solutions to the Einstein vacuum equations and the limits of these solutions. In particular, we focus on two conjectures of Burnett, which attempt to give an exact characterization of high-frequency limits of vacuum spacetimes as solutions to the Einstein-massless Vlasov system. Some open pr

Ludovic Goudenège, Andrea Molent, Xiao Wei, Antonino Zanette

This paper extends the valuation and optimal surrender framework for variable annuities with guaranteed minimum benefits in a L\'evy equity market environment by incorporating a stochastic interest rate described by the Hull-White model. This approach frames a more dynamic and realistic financial setting compared to previous literature. We exploit a robust v

Pawel Caputa, Krzysztof Kutak

We point out an interesting connection between the mathematical framework of the Krylov basis, which is used to quantify quantum complexity, and the entanglement entropy in high-energy QCD. In particular, we observe that the cascade equation of the dipole model is equivalent to the $SL(2,R)$ Schrodinger equation in the Krylov basis. Consequently, the Krylov

Brian McReynolds, Rui Graca, Lucas Kulesza, Peter McMahon-Crabtree

Biologically inspired event-based vision sensors (EVS) are growing in popularity due to performance benefits including ultra-low power consumption, high dynamic range, data sparsity, and fast temporal response. They efficiently encode dynamic information from a visual scene through pixels that respond autonomously and asynchronously when the per-pixel illumi

Nicolas Perez, Armand Leclerc, Guillaume Laibe, Pierre Delplace

Topological properties of the spectrum of shallow-water waves on a rotating spherical body are established. Particular attention is paid to its spectral flow, i.e. the modes whose frequencies transit between the Rossby and inertia-gravity wavebands as the zonal wave number is varied. Organising the modes according to the number of zeros of their meridional v

Johannes B. Gruber, Maximilian Weber

rollama is an R package that wraps the Ollama API, which allows you to run different Generative Large Language Models (GLLM) locally. The package and learning material focus on making it easy to use Ollama for annotating textual or imagine data with open-source models as well as use these models for document embedding. But users can use or extend rollama to

Luca Biferale, Fabio Bonaccorso, Moritz Linkmann, Damiano Capocci

We present TURB-Hel, a database formed by two datasets of incompressible homogeneous and isotropic turbulence, maintained in a statistically stationary state by fully helical forcing. The aim is to provide a dataset that clearly exhibits the phenomenon of the helicity cascade from the large to the small scales generated by a large-scale forcing that breaks t

Meinolf Geck, Alexander Lang

Let $\mathfrak{g}$ be a finite-dimensional simple Lie algebra over $\mathbb{C}$. In the 1950s Chevalley showed that $\mathfrak{g}$ admits particular bases, now called ``Chevalley bases'', for which the corresponding structure constants are integers. Such bases are not unique but, using Lusztig's theory of canonical bases, one can single out a ``canonical'' C

Rozane Bezerra dde Siqueira, Jose Ricardo Bezerra Nogueira, Carlos Feitosa Luna

This paper analyzes the redistributive impacts of indirect taxation reforms in Brazil inspired by PEC 45/2019, particularly in the version that led to EC 132/2023. Comparisons are made between the current system and the simulated reforms, considering the distribution of the tax burden among families in different income classes, as well as the impact on pover

Sara Cavallero, Fabio Saggese, Junya Shiraishi, Shashi Raj Pandey

We consider a setup with Internet of Things (IoT), where a base station (BS) collects data from nodes that use two different communication modes. The first is pull-based, where the BS retrieves the data from specific nodes through queries. In addition, the nodes that apply pull-based communication contain a wake-up receiver: upon a query, the BS sends wake-u

Tashmoy Ghosh

In this paper we have present an improved Cycle GAN based model for under water image enhancement. We have utilized the cycle consistent learning technique of the state-of-the-art Cycle GAN model with modification in the loss function in terms of depth-oriented attention which enhance the contrast of the overall image, keeping global content, color, local te

Matthew Rowe, Roman Zwicky

Based on explicitly gauge invariant interpolating operators we compute complete next-leading order QED-corrections for leptonic decays. These are sizeable since the helicity-suppression in V-A interactions allows for structure-dependent collinear logs. We have explicitly checked that these logs are absent for helicity-unsuppressed Yukawa-type transitions. Ba

Nathan Godey, Éric de la Clergerie, Benoît Sagot

Recent advances in language modeling consist in pretraining highly parameterized neural networks on extremely large web-mined text corpora. Training and inference with such models can be costly in practice, which incentivizes the use of smaller counterparts. However, it has been observed that smaller models can suffer from saturation, characterized as a drop

Pietro Freni

It is well known that ordered exponential fields with a compatible non-trivial valuation cannot be spherically complete, but there are some that are ``complete enough''. This paper gives analogues of Kaplansky's theorem on maximally valued fields that hold for a suitable class of elementary extensions of some ordered exponential fields with a com

Soumyabrata Chaudhuri, Saumik Bhattacharya

Skeleton Action Recognition (SAR) involves identifying human actions using skeletal joint coordinates and their interconnections. While plain Transformers have been attempted for this task, they still fall short compared to the current leading methods, which are rooted in Graph Convolutional Networks (GCNs) due to the absence of structural priors. Recently,

Bin Zhang, Zexin Peng, Bi Zeng, Junjie Lu

Due to budgetary constraints, indoor navigation typically employs 2D LiDAR rather than 3D LiDAR. However, the utilization of 2D LiDAR in Simultaneous Localization And Mapping (SLAM) frequently encounters challenges related to motion degeneracy, particularly in geometrically similar environments. To address this problem, this paper proposes a robust, accurate

Adi Harchol, Shahar Zuri, Esther Ritov, Faris Horani

The exploration of two-dimensional (2D) antiferromagnetic (AFM) materials has shown great promise and interest in tuning the magnetic and electronic properties as well as studying magneto-optical effects. The current work investigates the control of magneto-optical interactions in alloyed MnxZn1-xPS3 lamellar semiconductor single crystals, with the Mn/Zn rat

Marcus Witt, G. H. Philipp Nguyen, Josefine R. von Puttkamer-Luerssen, Can H. Yilderim

We study poly-crystalline spherical drops of an aqueous suspension of highly charged colloidal spheres exposed to a colloid-free aqueous environment. Crystal contours were obtained from standard optical imaging. The crystal spheres first expand to nearly four times their initial volume before slowly shrinking due to dilution-induced melting. Exploiting coher

Hanna Bartel, Joshua Lampert, Hendrik Ranocha

A common way to numerically solve Fokker-Planck equations is the Chang-Cooper method in space combined with one of the Euler methods in time. However, the explicit Euler method is only conditionally positive, leading to severe restrictions on the time step to ensure positivity. On the other hand, the implicit Euler method is robust but nonlinearly implicit.

Saurav Sen, Bhaswati Mookerjea, Rolf Guesten, Friedrich Wyrowski

Hub-filament systems (HFSs) being the potential sites of formation of star clusters and high mass stars, provide a test bed for the current theories that attempt to explain star formation globally. It is thus important to study a large number of HFSs using both intensity and velocity information to constrain these objects better observationally. We present h

Rico Pohle, Nic Shannon, Yukitoshi Motome

Multipolar spin systems provide a rich ground for the emergence of unexpected states of matter due to their enlarged spin degree of freedom. In this study, with a specific emphasis on $S=1$ magnets, we explore the interplay between spin nematic states and spin liquids. Based on the foundations laid in the prior work [R. Pohle et al., Phys. Rev. B 107, L14040

Tony J. Puthenpurakal

Let $(A,\mathfrak{m})$ be an analytically unramified Cohen-Macaulay local ring of dimension $d \geq 3$ and let $\mathfrak{a}$ be an $\mathfrak{m}$-primary ideal in $A$. If $I$ is an ideal in $A$ then let $I^*$ be the integral closure of $I$ in $A$. Let $G_{\mathfrak{a}}(A)^* = \bigoplus_{n\geq 0 }(\mathfrak{a}^n)^*/(\mathfrak{a}^{n+1})^*$ be the associated g

Miguel A. Cascales Sandoval, A. Hierro-Rodríguez, S. Ruiz-Gómez, L. Skoric

Chiral magnetic textures are key for the development of modern spintronic devices. In multilayered thin films, these are typically stabilized via the interfacial intralayer Dzyaloshinskii-Moriya interaction (DMI). Additionally, it has been recently observed that DMI may also promote vector spin chirality along the third dimension, coupling spins in different

Igor D. Karachentsev, Valentina E. Karachentseva, Serafim S. Kaisin, Chuan-Peng Zhang

{We report the discovery of 20 new dwarf galaxies in the Local Volume identified as optical counterparts to the Five-hundred-meter Aperture Spherical radio Telescope (FAST) All Sky HI Survey (FASHI) sources. The galaxies have a median stellar mass of $7.8\times 10^6~M_{\odot}$ and a median HI mass of $1.0\times 10^7~M_{\odot}$. Most of them are field galaxie

Yuxia Yuan, Markus Ryll

Modeling the kinematics and dynamics of robotics systems with suspended loads using dual quaternions has not been explored so far. This paper introduces a new innovative control strategy using dual quaternions for UAVs with cable-suspended loads, focusing on the sling load lifting and tracking problems. By utilizing the mathematical efficiency and compactnes

Souhaila Boublouh, Miguel Suarez, Gao Feng, Abderrahmane Belkhir

In this article, we present an experimental study supported by numerical modeling showing the possibility of exciting Symmetry-Protected Bound states In the Continuum (SP-BICs) in a 1D silicon grating fabricated on a lithium niobate substrate in both transverse electric and transverse magnetic polarization states of the incident illumination. This leads to d

Max Tymczyszyn, Edward McCann

We describe the mean-field model of a one-dimensional topological superconductor with two orbitals per unit cell. Time-reversal symmetry is absent, but a nonsymmorphic symmetry, involving a translation by a fraction of the unit cell, mimics the role of time-reversal symmetry. As a result, the topological superconductor has $\mathbb{Z}_4$ topological phases,

Marc Hallin, Simos G. Meintanis, Klaus Nordhausen

We propose a family of tests of the validity of the assumptions underlying independent component analysis methods. The tests are formulated as L2-type procedures based on characteristic functions and involve weights; a proper choice of these weights and the estimation method for the mixing matrix yields consistent and affine-invariant tests. Due to the compl

Eleonora Ficola, Thomas Schmidt

We study the minimization of anisotropic total variation functionals with additional measure terms among functions of bounded variation subject to a Dirichlet boundary condition. More specifically, we identify and characterize certain isoperimetric conditions, which prove to be sharp assumptions on the signed measure data in connection with semicontinuity, e

Jinzhi Lu, Pingyang Gao

We investigate investors voluntary disclosure decisions under uncertainty about their information endowment (Dye 1985). In our model, an investor may receive initial evidence about a target firm. Conditional on learning the initial evidence, the investor may receive additional evidence that helps interpret the initial evidence. The investor takes a position

Anna Zakharova

The symmetric top molecule YbOCH$_3$ is studied for its potential to $\mathcal{P}$, $\mathcal{T}$-violation searches. The influence of the rotations and vibrations of the YbOCH$_3$ on such violating effects as the electron electric dipole moment (eEDM) and the scalar-pseudoscalar electron-nucleon interaction (Ne-SPS) is studied using the coupled channels met

Szczepan Głodzik, Rok Žitko

Since the seminal works in the fifties it has been known that a bath of non-interacting electrons mediates an interaction between local moments (such as nuclear spins or magnetic impurities) coupled to distant sites of the lattice. Recent efforts in simultaneous control of multi-qubit arrays rely on defining quantum dots in environments which likewise contai

Shan Wang, Chuong Nguyen, Jiawei Liu, Kaihao Zhang

Reliable segmentation of road lines and markings is critical to autonomous driving. Our work is motivated by the observations that road lines and markings are (1) frequently occluded in the presence of moving vehicles, shadow, and glare and (2) highly structured with low intra-class shape variance and overall high appearance consistency. To solve these issue

Finn M. Stokes, Benjamin J. Owen, Waseem Kamleh, Derek B. Leinweber

The parity-expanded variational analysis (PEVA) technique enables the isolation of opposite-parity eigenstates at finite momentum. The approach has been used to perform the first lattice QCD calculations of excited-baryon form factors. In particular, these calculations show that the low-lying odd-parity nucleon excitations are described well by constituent q

Uwe Naumann

The efficient computation of Jacobians represents a fundamental challenge in computational science and engineering. Large-scale modular numerical simulation programs can be regarded as sequences of evaluations of in our case differentiable subprograms with corresponding elemental Jacobians. The latter are typically not available. Tangent and adjoint versions

Anna Mastikhina, Oleg Senkevich, Dmitry Sirotkin, Danila Demin

This paper examines the graph partition problem and introduces a new metric, MSIDS (maximal sum of inner degrees squared). We establish its connection to the replication factor (RF) optimization, which has been the main focus of theoretical work in this field. Additionally, we propose a new partition algorithm, DBH-X, based on the DBH partitioner. We demonst

David Dolžan

We prove that a semiring multiplicatively generated by its idempotents is commutative and Boolean, if every idempotent in the semiring has an orthogonal complement. We prove that a semiring additively generated by its idempotents is commutative, if every idempotent in the semiring has an orthogonal complement and all the nilpotents in the semirings are centr

Jun Li, Su Hwan Kim, Philip Müller, Lina Felsner

This research explores the integration of language models and unsupervised anomaly detection in medical imaging, addressing two key questions: (1) Can language models enhance the interpretability of anomaly detection maps? and (2) Can anomaly maps improve the generalizability of language models in open-set anomaly detection tasks? To investigate these questi

Zoltán Bajnok, János Balog, István Vona

Perturbation theory in asymptotically free quantum field theories is asymptotic. The factorially growing perturbative coefficients carry information about non-perturbative corrections, which can be related to renormalons and instantons. Using the Wiener-Hopf technique we determine the full analytic solution for the free energy density in the two dimensional

Yue Gou, Yuming Xing, Shengzhu Shi, Zhichang Guo

Accurately segmenting the pancreas remains a huge challenge. Traditional methods encounter difficulties in semantic localization due to the small volume and distorted structure of the pancreas, while deep learning methods encounter challenges in obtaining accurate edges because of low contrast and organ overlapping. To overcome these issues, we propose a mul

Vitalijs Brejevs, Peter Feller

The twisting number of a ribbon knot $K$ is the minimal number of tangle replacements on the symmetry axis of $J \# -J$ for any knot $J$ that is required to produce a symmetric union diagram of $K$. We prove that the twisting number is bounded below by the doubly slice genus and produce examples of ribbon knots with arbitrarily high twisting number, addressi

Zengjing Chen, Panyu Wu, Xiaowen Zhou

We consider a class of stochastic control problems which has been widely used in optimal foraging theory. The state processes have two distinct dynamics, characterized by two pairs of drift and diffusion coefficients, depending on whether it takes values bigger or smaller than a threshold value. Adopting a perturbation type approach, we find an expression fo

Fumio Hiai, Anna Jenčová

We study the $\alpha$-$z$-R\'enyi divergences $D_{\alpha,z}(\psi\|\varphi)$ where $\alpha,z>0$ ($\alpha\ne1$) for normal positive functionals $\psi,\varphi$ on general von Neumann algebras, introduced in [S.~Kato and Y.~Ueda, arXiv:2307.01790] and [S.~Kato, arXiv:2311.01748]. We prove the variational expressions and the data processing inequality (DPI) for t

Arushi Goel, Zhifeng Kong, Rafael Valle, Bryan Catanzaro

Existing datasets for audio understanding primarily focus on single-turn interactions (i.e. audio captioning, audio question answering) for describing audio in natural language, thus limiting understanding audio via interactive dialogue. To address this gap, we introduce Audio Dialogues: a multi-turn dialogue dataset containing 163.8k samples for general aud

Chengpeng Hu, Yunlong Zhao, Jialin Liu

Recently, the emergence of large language models (LLMs) has unlocked new opportunities for procedural content generation. However, recent attempts mainly focus on level generation for specific games with defined game rules such as Super Mario Bros. and Zelda. This paper investigates the game generation via LLMs. Based on video game description language, this

Mark Jerrum

The hard-core model has as its configurations the independent sets of some graph instance $G$. The probability distribution on independent sets is controlled by a `fugacity' $\lambda>0$, with higher $\lambda$ leading to denser configurations. We investigate the mixing time of Glauber (single-site) dynamics for the hard-core model on restricted classes of bou

Erasmo Caponio, Antonio Masiello, Stefan Suhr

We consider a differential inclusion on a manifold, defined by a field of open half-spaces whose boundary in each tangent space is the kernel of a one-form. We make the assumption that the corank one distribution associated to the kernel is completely nonholonomic of step 2. We identify a subset of solutions of the differential inclusion, satisfying two endp

Iker García-Ferrero, Rodrigo Agerri, Aitziber Atutxa Salazar, Elena Cabrio

Research on language technology for the development of medical applications is currently a hot topic in Natural Language Understanding and Generation. Thus, a number of large language models (LLMs) have recently been adapted to the medical domain, so that they can be used as a tool for mediating in human-AI interaction. While these LLMs display competitive p

Zilong Liu, Krzysztof Janowicz, Kitty Currier, Meilin Shi

Generative AI based on foundation models provides a first glimpse into the world represented by machines trained on vast amounts of multimodal data ingested by these models during training. If we consider the resulting models as knowledge bases in their own right, this may open up new avenues for understanding places through the lens of machines. In this wor

Iker García-Ferrero, Begoña Altuna

We present NoticIA, a dataset consisting of 850 Spanish news articles featuring prominent clickbait headlines, each paired with high-quality, single-sentence generative summarizations written by humans. This task demands advanced text understanding and summarization abilities, challenging the models' capacity to infer and connect diverse pieces of informatio

Minkuk Kim, Hyeon Bae Kim, Jinyoung Moon, Jinwoo Choi

There has been significant attention to the research on dense video captioning, which aims to automatically localize and caption all events within untrimmed video. Several studies introduce methods by designing dense video captioning as a multitasking problem of event localization and event captioning to consider inter-task relations. However, addressing bot

Changxin Liu, Xiao Tan, Xuyang Wu, Dimos V. Dimarogonas

Constraint satisfaction is a critical component in a wide range of engineering applications, including but not limited to safe multi-agent control and economic dispatch in power systems. This study explores violation-free distributed optimization techniques for problems characterized by separable objective functions and coupling constraints. First, we incorp

Yongming Li, Xikui Ma, Xuchen Wang, Sergei A. Tretyakov

In this paper, we present a general theory of aperiodic subwavelength arrays for controlling electromagnetic waves. The considered platform is formed by an array of electrically small loaded scatterers above a ground plane. While the array is geometrically periodic, all the loads can be in general different, so that the distributions of currents induced by p

M. Jaleed Khan, Ioana Duta, Beth Albert, William Cooke

The rapid advancement of Artificial Intelligence (AI) in healthcare presents a unique opportunity for advancements in obstetric care, particularly through the analysis of cardiotocography (CTG) for fetal monitoring. However, the effectiveness of such technologies depends upon the availability of large, high-quality datasets that are suitable for machine lear

Ollie Ballinger

Despite extensive research into ship detection via remote sensing, no studies identify ship-to-ship transfers in satellite imagery. Given the importance of transshipment in illicit shipping practices, this is a significant gap. In what follows, I train a convolutional neural network to accurately detect 4 different types of cargo vessel and two different typ

Yahel Manor, Or Meir

Lifting theorems are theorems that bound the communication complexity of a composed function $f\circ g^{n}$ in terms of the query complexity of $f$ and the communication complexity of $g$. Such theorems constitute a powerful generalization of direct-sum theorems for $g$, and have seen numerous applications in recent years. We prove a new lifting theorem that

Lucas Dedieu, Nicolas Nerrienet, Adrien Nivaggioli, Clara Simmat

Recent advancements in deep learning have proven highly effective in medical image classification, notably within histopathology. However, noisy labels represent a critical challenge in histopathology image classification, where accurate annotations are vital for training robust deep learning models. Indeed, deep neural networks can easily overfit label nois

Rohan R. Pote, Bhaskar D. Rao

We propose a novel sensing approach for the beam alignment problem in millimeter wave systems using a single Radio Frequency (RF) chain. Conventionally, beam alignment using a single phased array involves comparing beamformer output power across different spatial regions. This incurs large training overhead due to the need to perform the beam scan operation.

Jihao Liu, Jinliang Zheng, Yu Liu, Hongsheng Li

This paper proposes a GeneraLIst encoder-Decoder (GLID) pre-training method for better handling various downstream computer vision tasks. While self-supervised pre-training approaches, e.g., Masked Autoencoder, have shown success in transfer learning, task-specific sub-architectures are still required to be appended for different downstream tasks, which cann

Vineet Kumar, Suresh Sundaram

Writer identification due to its widespread application in various fields has gained popularity over the years. In scenarios where optimum handwriting samples are available, whether they be in the form of a single line, a sentence, or an entire page, writer identification algorithms have demonstrated noteworthy levels of accuracy. However, in scenarios where

Thomas Appelquist, James Ingoldby, Maurizio Piai

Dilaton effective field theory (dEFT) describes the long distance behavior of certain confining, near-conformal gauge theories that have been studied via lattice computation. Pseudo-Nambu-Goldstone bosons (pNGBs), emerging from the breaking of approximate, continuous, internal symmetries, are coupled to an additional scalar particle, the dilaton, arising fro

Hefeng Wang, Jiale Cao, Jin Xie, Aiping Yang

Text-to-image diffusion models have shown powerful ability on conditional image synthesis. With large-scale vision-language pre-training, diffusion models are able to generate high-quality images with rich texture and reasonable structure under different text prompts. However, it is an open problem to adapt the pre-trained diffusion model for visual percepti

Geunsu Choi, Mingu Jung, Han Ju Lee, Oscar Roldan

We solve two main questions on linear structures of (non-)norm-attaining Lipschitz functions. First, we show that for every infinite metric space $M$, the set consisting of Lipschitz functions on $M$ which do not strongly attain their norm and the zero contains an isometric copy of $\ell_\infty$, and moreover, those functions can be chosen not to attain thei

Zhengqing He, Lun Qu, Wei Wu, Jikun Liu

Tunable nonlinearity facilitates the creation of reconfigurable nonlinear metasurfaces, enabling innovative applications in signal processing, light switching, and sensing. This paper presents a novel approach to electrically modulate SHG from a lithium niobate (LN) metasurface, exploiting the electro-optical (EO) effect. By fabricating a nanohole array meta

Aaron D. Spector, Todd Kozlowski

We describe a technique for measuring the complex reflectivity of an optical cavity with a resonant local oscillator laser and an auxiliary probe laser, each coupled via opposite ends of the cavity. A heterodyne sensing scheme is then used to observe the phase and amplitude of the interference beat-note between the promptly reflected field and the cavity tra

Boris Kazarnovskii

We define integral geometric analogues of the Chern classes for real vector bundle on a smooth real variety. More precisely, we define the Chern densities of a real bundle. These densities are analogues of the Chern forms of a complex vector bundle and inherit some of their properties. \noindent (The text is a summary of a report on the conference PCA'2024 i

Yoshimasa Hidaka, Yuya Tanizaki, Arata Yamamoto

We propose the $(3+1)$-dimensional $\mathbb{Z}_3$ lattice gauge theory coupled with the 2-flavor Wilson-Dirac fermion as a toy model for studying quantum chromodynamics (QCD) at nonzero density. We study its phase diagram in the space of the lattice gauge couplings $g^2$ and the quark chemical potentials $\mu$ and discuss the similarity and difference compar

Olatunji Mumini Omisore, Toluwanimi Akinyemi, Anh Nguyen, Lei Wang

Robot-assisted catheterization has garnered a good attention for its potentials in treating cardiovascular diseases. However, advancing surgeon-robot collaboration still requires further research, particularly on task-specific automation. For instance, automated tool segmentation can assist surgeons in visualizing and tracking of endovascular tools during ca

Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort, Sylvain Le Corff

Identifying the parameters of a non-linear model that best explain observed data is a core task across scientific fields. When such models rely on complex simulators, evaluating the likelihood is typically intractable, making traditional inference methods such as MCMC inapplicable. Simulation-based inference (SBI) addresses this by training deep generative m